Yield prediction in wheat (Triticum aestivum L.) using spectral reflectance indices

Current Science

Volumn 116, Issue 2, 2019, Pages 272-278

  Chandel, N S ^a   Tiwari, P S ^a   Singh, K P ^a   Jat, D ^a   Gaikwad, B B ^a   Tripathi, H ^a   Golhani, K ^a  

^a CENTRAL INSTITUTE OF AGRICULTURAL ENGINEERING   (India)

Author keywords

Nitrogen management; Spectral reflectance; Vegetation indices; Wheat; Yield estimation

Indexed keywords

EID: 85060470219     PISSN: 00113891     EISSN: None     Source Type: Journal    
DOI: 10.18520/cs/v116/i2/272-278     Document Type: Article

References (25)

1. Li, F. et al., Estimating N status of winter wheat using a handheld spectrometer in the North China Plain. Field Crops Res., 2008, 106(1), 77-85
2. Hansen, P. M. and Schjoerring, J. K., Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least square regression. Remote Sensing Environ., 2002, 86, 542-553
3. Clay, D. E., Kim, K. I., Chang, J., Clay, S. A. and Dalsted, K., Characterizing water and nitrogen stress in corn using remote sensing. Agron. J., 2006, 98, 579-587
4. Zhang, J. H., Wang, K., Bailey, J. S. and Wang, R. C., Predicting nitrogen status of rice using multispectral data at canopy scale. Pedosphere, 2006, 16, 108-117
5. Scharf, P. C., Schmidt, J. P., Kitchen, N. R., Sudduth, K. A., Hong, S. Y., Lory, J. A. and Davis, J. G., Remote sensing for nitrogen management. J. Soil Water Conserv., 2002, 57(6), 518-524
6. Jia, L. L., Buerkert, A., Chen, X. P., Romheld, V. and Zhang, F. S., Low altitude aerial photography for optimum N fertilization of winter wheat on the North China Plain. Field Crops Res., 2004, 89, 389-395
7. Osborne, S. L., Schcpcr, J. S., Frdncis, D. D. and Schlcmmcr, M. R., Detection of phosphorous and nitrogen deficiencies in corn using spectral radiance measurement. Agronomy J., 2002, 94, 1215-1221
8. Goel, P. K., Prasher, S. O., Landry, J. A., Patel, R. M., Bonnell, R. B., Viau, A. A. and Millerm J. R., Potential of airborne hyperspectral remote sensing to detect nitrogen deficiency and weed infestation in corn. Comput. Electron. Agric., 2003, 38(2), 99-114
9. Lawrence, R. L. and Ripple, W. J., Comparisons among vegetation indices and bandwise regression in a highly disturbed, heterogeneous landscape: Mount St. Helens, Washington. Remote Sensing Environ., 1998, 64(1), 91-102
10. Shibayama, M. and Akiyama, T., Estimating grain yield of maturing rice canopies using high spectral resolution reflectance measurements. Remote Sensing Environ., 1991, 36, 45-53
11. Laudien, R., Burky, K., Doluschitz, R. and Bareth, G., Establishment of a web-based spectral database for the analysis of hyperspectral data from Rhizoctonia solani-inoculated sugarbeets. Sugar Ind., 2006, 131(3), 164-170
12. Pradhan, S., Bandyopadhyaya, K. K. and Joshi, D. K., Canopy reflectance spectra of wheat as related to crop yield, grain protein under different management practices. J. Agrometeorol., 2012, 14(1), 21-25
13. Zuzna, M., Frantisek, Z. and Kvet, J., Normalized difference vegetation index (NDVI) in the management of mountain meadows. Boreal Environ. Res., 2008, 13, 147-432
14. Huete, A. R., A soil adjusted vegetation index (SAVI). Remote Sensing Environ., 1988, 17, 37-53
15. Gontia, N. and Tiwari, K., Yield estimation model and water productivity of wheat crop (Triricum aestivum) in an irrigated command using remote sensing and GIS. J. Indian Soc. Remote Sensing, 2011, 39(1), 27-37
16. Gao, B., NDWI a normalized difference water index for remote sensing of vegetation liquid water from Space. Remote Sensing Environ., 1996, 58, 257-266
17. Serrano, L., Penuelasa, J. and Ustin, S., Remote sensing of nitrogen and lignin in Mediterranean vegetation from AV1RIS data: decomposing biochemical from structural signals. Remote Sensing Environ., 2002, 81, 355-364
18. Baethgen, W. E. and Alley, M. M., Optimizing soil and fertilizer nitrogen use by intensively managed winter wheat. II. Critical levels and optimum rates of nitrogen fertilizer. Agron. J., 1989, 81, 120-125
19. Gnyp, M. L. et al., Hyperspectral data analysis of nitrogenfertilization effect on winter wheat using spectrometer in North China Plain. In Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, First Workshop of IEEE, 2009, pp. 1-4
20. Prasad, B., Carver, B., Stone, M. L., Babar, M. A., Raun, W. R. and Klatt and A. R., Potential use of spectral reflectance indices as a selection tool for grain yield in winter wheat under great plains conditions. Crop Sci., 2007, 47, 1426-1440
21. Lukina, E. V. et al., Effect of row spacing, growth stage, and nitrogen rate on spectral irradiance in winter wheat. J. Plant Nutr., 2000, 23, 103-122
22. Weisz, R., Crozier, C. R. and Heiniger, R. W., Optimizing nitrogen application timing in no-till soft red winter wheat. Agron. J., 2001, 93, 435-442
23. Arnall, D. B. et al., Relationship between coefficient of variation measured by spectral reflectance and plant density at early growth stages in winter wheat. J. Plant Nutr., 2006, 29, 1983-1997
24. Raun, W. R., Johnson, G. V., Stone, M. L., Solie, J. B., Lukina, E. V., Thomason, W. E. and Schepers, J. S., In-season prediction of potential grain yield in winter wheat using canopy reflectance. Agron. J., 2001, 93, 131-138
25. Rouse, J. W., Haas, R. H., Schell, J. A., Deering, D. W. and Harlan, J. C., Monitoring the vernal advancements and retrogradation of natural vegetation. In NASA/GSFC Final Report, Greenbelt, MD, USA, 1974, pp. 1-37